From Science to e-Science to Semantic e-Science: A Heliosphysics Case Study

The past few years have witnessed unparalleled efforts to make scientific data web accessible. The Semantic Web has proven invaluable in this effort; however, much of the literature is devoted to system design, ontology creation, and trials and tribulations of current technologies. In order to fully develop the nascent field of Semantic e-Science we must also evaluate systems in real-world settings. We describe a case study within the field of Heliophysics and provide a comparison of the evolutionary stages of data discovery, from manual to semantically enable. We describe the socio-technical implications of moving toward automated and intelligent data discovery. In doing so, we highlight how this process enhances what is currently being done manually in various scientific disciplines. Our case study illustrates that Semantic e-Science is more than just semantic search. The integration of search with web services, relational databases, and other cyberinfrastructure is a central tenet of our case study and one that we believe has applicability as a generalized research area within Semantic e-Science. This case study illustrates a specific example of the benefits, and limitations, of semantically replicating data discovery. We show examples of significant reductions in time and effort enable by Semantic e-Science; yet, we argue that a "complete" solution requires integrating semantic search with other research areas such as data provenance and web services

GSFC Heliophysics Science Division 2008 Science Highlights

This report is intended to record and communicate to our colleagues, stakeholders, and the public at large about heliophysics scientific and flight program achievements and milestones for 2008, for which NASA Goddard Space Flight Center's Heliophysics Science Division (HSD) made important contributions. HSD comprises approximately 261 scientists, technologists, and administrative personnel dedicated to the goal of advancing our knowledge and understanding of the Sun and the wide variety of domains that its variability influences. Our activities include Lead science investigations involving flight hardware, theory, and data analysis and modeling that will answer the strategic questions posed in the Heliophysics Roadmap; Lead the development of new solar and space physics mission concepts and support their implementation as Project Scientists; Provide access to measurements from the Heliophysics Great Observatory through our Science Information Systems, and Communicate science results to the public and inspire the next generation of scientists and explorers

On the Role of Context and Subjectivity on Scientific Information Systems

The explicit representation of context and subjectivity enables an information system to support multiple interpretations of the data it records. This is a crucial aspect of learning and innovation within scientific information systems. We present an ontology-based framework for context and subjectivity that integrates two lines of research: data provenance and ontological foundations of the Semantic Web. Data provenance provides a set of constructs for representing data history. We extend the definition of these constructs in order to describe multiple viewpoints or interpretations held within a domain. The W7 model, the Toulmin model, and the Proof Markup Language (PML) provide the Interlingua for creating multiple viewpoints of data in a machine-readable and sharable form. Example use cases in space sciences are used to demonstrate the feasibility and value of our approach

The ESPAS e-infrastructure

ESPAS provides an e-Infrastructure to support access to a wide range of archived observations and model derived data for the near-Earth space environment, extending from the Earth's middle atmosphere up to the outer radiation belts. To this end, ESPAS will serve as a central access hub for researchers who wish to exploit multi-instrument multipoint data for scientific discovery, model development and validation, and data assimilation, among others. Observation based and model enhanced scientific understanding of the physical state of the Earth's space environment and its evolution is critical to advancing space weather and space climate studies, two very active branches of current scientific research. ESPAS offers an interoperable data infrastructure that enables users to find, access, and exploit near-Earth space environment observations from ground-based and spaceborne instruments and data from relevant models, obtained from distributed repositories. In order to facilitate efficient user queries ESPAS allows a highly flexible workflow scheme to select and request the desired data sets. ESPAS has the strategic goal of making Europe a leading player in the efficient use and dissemination of near-Earth space environment information offered by institutions, laboratories and research teams in Europe and worldwide, that are active in collecting, processing and distributing scientific data. Therefore, ESPAS is committed to support and foster new data providers who wish to promote the easy use of their data and models by the research community via a central access framework. ESPAS is open to all potential users interested in near-Earth space environment data, including those who are active in basic scientific research, technical or operational development and commercial applications

Toward a reference architecture based science gateway framework with embedded e‐learning support

Science gateways have been widely utilized by a large number of user communities to simplify access to complex distributed computing infrastructures. While science gateways are still becoming increasingly popular and the number of user communities is growing, the fast and efficient creation of new science gateways and the flexibility to deploy these gateways on-demand on heterogeneous computational resources, remain a challenge. Additionally, the increase in the number of users, especially with very different backgrounds, requires intuitive embedded e-learning tools that support all stakeholders to find related learning material and to guide the learning process. This paper introduces a novel science gateway framework that addresses these challenges. The framework supports the creation, publication, selection, and deployment of cloud-based reference architectures that can be automatically instantiated and executed even by nontechnical users. The framework also incorporates a knowledge repository exchange and learning module that provides embedded e-learning support. To demonstrate the feasibility of the proposed solution, two scientific case studies are presented based on the requirements of the plasmasphere, ionosphere, and thermosphere research communities